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Virtual certification of gas turbine engines - visualizing the DLR Rig250 compressor
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Prabhakar, Arun, Goddard, Christopher R., Amirantec, Dario, Reguly, Istvan Z., Gerstenberger, Axel, Suhrmann, Jan-Friedrich, Jarvis, Stephen A., Lapworth, Leigh and Mudalige, Gihan R. (2022) Virtual certification of gas turbine engines - visualizing the DLR Rig250 compressor. In: Supercomputing 2022 - Scientific Visualization and Data Analytics Showcase, Dallas, TX US, 14–17 Nov 2022
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PDF
WRAP-virtual-certification-gas-turbine-engines-visualizing-DLR-Rig250-compressor-Mudalige-2023.pdf - Accepted Version - Requires a PDF viewer. Download (18Mb) | Preview |
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Video (MPEG) (Scientific Visualization Showcase - Video)
Warwick_SciVis2022_Final_EmbeddedSubtitles.mp4 - Supplemental Material Download (328Mb) |
Official URL: https://sc22.supercomputing.org/presentation/?id=s...
Abstract
High Performance Computing (HPC) critically underpins the design of aero-engines. With global emissions targets, engine designs require a fundamental change including designs utilizing sustainable aviation fuels and electric/hybrid flight. Virtual certification of designs with HPC is recognized as a key technology to meet these challenges, but require analysis on models with higher fidelity, using ultra-large scale executions. In this explanatory SC-SciVis showcase, we present results from time-accurate simulations of a 4.6B-element full 360-degree model of a production-representative gas turbine engine compressor, the Rig250 at DLR. This represents a grand challenge problem, at the fidelity for virtual certification standards. The results are achieved through Rolls-Royce’s Hydra CFD suite on ARCHER2. The compressor is visualized under off-design conditions, demonstrating flow contours of velocity, Mach number and iso-surfaces of vorticity. The level of detail and the HPC simulations leading to the visualizations demonstrate a step-change towards achieving virtual certification objectives under production settings.
Item Type: | Conference Item (Other) | ||||||||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||||||
Library of Congress Subject Headings (LCSH): | High performance computing, Gas-turbines -- Simulation methods , Computational fluid dynamics | ||||||||||||
Official Date: | 14 November 2022 | ||||||||||||
Dates: |
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Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Free Access (unspecified licence, 'bronze OA') | ||||||||||||
Copyright Holders: | ACM | ||||||||||||
Date of first compliant deposit: | 29 January 2023 | ||||||||||||
Date of first compliant Open Access: | 31 January 2023 | ||||||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Other | ||||||||||||
Title of Event: | Supercomputing 2022 - Scientific Visualization and Data Analytics Showcase | ||||||||||||
Type of Event: | Conference | ||||||||||||
Location of Event: | Dallas, TX US | ||||||||||||
Date(s) of Event: | 14–17 Nov 2022 | ||||||||||||
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Open Access Version: |
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